Learning Model for Phishing Website Detection

• DOI: 10.4108/eai.13-7-2018.163804
• Publication Date: 2020-03-13T13:37:42Z
• Authors: A. Suryan; C. Kumar; M. Mehta; R. Juneja; A. Sinha
• Keywords: machine learning; classification; T58.6-58.62; feature extraction; 0202 electrical engineering, electronic engineering, information engineering; phishing; security; Management information systems; 02 engineering and technology; information systems; dimensionality reduction

Website portal empowered with information technology are of great importance in present scenario. With access to data allaround the world, securing our information becomes an issue of topmost priority. Over the decade there have beennumerous attacks by phishing websites and people have lost huge resources. Such malicious websites, also known asphishing website, steal information of authenticate users and carry out illegal transactions by misusing the personalinformation. Phishing website links and associated e-mails are sent to billions of users daily, thereby becoming a bigconcern for cyber security. In this paper, we address the phishing problem using machine learning approach applied on ourproposed model, which uses 30 distinct features for phishing detection. We extracted multiple features from the websitelink and applied appropriate algorithms to classify the link as legitimate or phishing links.